A general optimization solver based on OP-to-MaxSAT reduction
Yuxin Zhao, Han Huang, Zhifeng Hao

TL;DR
This paper introduces GORED, a unified optimization solver that reduces various optimization problems to MaxSAT, enabling broad applicability and comparable solution quality across diverse problem types.
Contribution
The paper presents OP-to-MaxSAT reduction and a general solver, GORED, which unifies solving multiple optimization problems through polynomial-time reduction to MaxSAT.
Findings
Successfully solves 136 instances across 11 problem types.
Achieves solution quality comparable to specialized methods.
Demonstrates broad applicability and efficiency of the reduction approach.
Abstract
Optimization problems are fundamental in diverse fields, such as engineering, economics, and scientific computing. However, current algorithms are mostly designed for specific problem types and exhibit limited generality in solving multiple types of optimization problems. To enhance generality, we propose an automated reduction method named OP-to-MaxSAT reduction and a general optimization solver based on OP-to-MaxSAT reduction (GORED). GORED unifies the solving of multiple types of optimization problems by reducing the problems from optimization problems to MaxSAT instances in polynomial time and solving them using the state-of-the-art MaxSAT solver. The generality and solution quality of GORED are validated through experiments on 136 instances across 11 types of optimization problems. Experimental results demonstrate that GORED not only successfully solves a wide range of optimization…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
